c2c 1.0.3

Convert directory structure into a single text file while respecting .gitignore rules

c2c

A Python package that converts a directory structure into a single text file, preserving file contents and directory hierarchy while respecting .gitignore rules. Perfect for sharing codebase context with AI language models or creating project snapshots.

Features

• Smart Directory Scanning: Recursively scans directories and outputs contents as a single well-formatted text file with clear delimiters between files
• Git-Aware:
  • Fully respects .gitignore rules at both root and subdirectory levels
  • Handles negative patterns (patterns starting with !) correctly
  • Supports multiple .gitignore files in subdirectories, just like Git
• Intelligent File Handling:
  • Automatically detects and excludes binary files to maintain output integrity
  • Full UTF-8 encoding support with proper error handling
  • Generates unique, collision-free delimiters to clearly separate files
• Flexible Configuration:
  • Custom exclude patterns via command line arguments or Python API
  • Debug mode for troubleshooting pattern matching
  • Easy integration with both CLI and Python applications
• AI-Ready Output:
  • Generates output specifically formatted for optimal use with AI language models
  • Supports large language models like Claude, GPT-4, etc.
  • Preserves directory structure and file relationships for better context

Installation

Install from PyPI:

pip install c2c

Or install from source:

git clone https://github.com/kawataki-yoshika/c2c.git
cd c2c
pip install .

Usage

Command Line Interface

Basic usage - scan current directory:

c2c .

Scan specific directory:

c2c /path/to/directory

Exclude specific patterns:

c2c . -e "*.log" -e "temp/*"

Enable debug mode to see pattern matching details:

c2c . --debug

Save output to file:

c2c . > project_snapshot.txt

Python API

The package provides a flexible Python API for integration into your tools:

from c2c import scan_directory, create_delimiter

# Generate a unique delimiter
delimiter = create_delimiter()

# Basic usage with default excludes
scan_directory(
    directory=".",
    exclude_patterns=[".git"],  # Default exclude pattern
    delimiter=delimiter
)

# With custom exclude patterns
scan_directory(
    directory="/path/to/project",
    exclude_patterns=[
        ".git",  # Default
        "*.log",
        "temp/*"
    ],
    delimiter=delimiter,
    debug=True
)

Using with AI Language Models

1. Generate a snapshot of your project:

c2c . > context.txt

2. Use in your prompts:

Here's my project structure and contents:

[paste contents of context.txt]

Could you help me understand the code structure and suggest improvements?

The output format is specifically designed to help AI models understand:

• Project structure and hierarchical relationships
• File contents with clear, unambiguous boundaries
• Complete directory hierarchy and organization
• Metadata about excluded files and patterns

Output Format

The generated output follows this structure:

# Project Directory Contents
# Format: Files are separated by a delimiter line starting with "### FILE_[uuid]"
# Each delimiter line is followed by the file path, then the file contents.
# Note: Binary files and patterns matching any .gitignore are excluded.

# DELIMITER=### FILE_[uuid]

### FILE_[uuid] src/main.py
[contents of main.py]

### FILE_[uuid] src/utils/helper.py
[contents of helper.py]

Default Excludes

By default, c2c excludes:

• .git directories and all Git-related files
• Binary files (automatically detected)
• Files matching any .gitignore patterns

You can add additional patterns using the -e flag or through the Python API.

Advanced Features

GitignoreRule Handling

The GitignoreRule system provides full Git-compatible pattern matching:

• Base directory-specific patterns for scoped ignores
• Negative patterns with ! for pattern negation
• Path matching with / prefix for root-relative patterns
• Directory-only patterns (ending with /)
• Pattern normalization and **/ pattern support

Binary File Detection

• Smart UTF-8 decoding attempt to detect binary files
• Configurable detection threshold
• Ensures output integrity by excluding non-text content
• Proper handling of various text encodings

Gitignore Processing

• Multiple .gitignore files support with proper precedence rules
• Pattern processing order matches Git behavior
• Scoped rules based on .gitignore file location
• Full support for pattern negation and complex rule combinations

Contributing

We welcome contributions! Here's how you can help:

• Submit pull requests for bug fixes or new features
• Report bugs and suggest improvements
• Improve documentation and examples
• Share use cases and feature ideas

Please feel free to open issues or submit pull requests on GitHub.

License

This project is licensed under the MIT License - see the LICENSE file for details.